On Lagrange Multiplier Tests in Multidimensional Item Response Theory: Information Matrices and Model Misspecification

Autor/inn/en	Falk, Carl F.; Monroe, Scott
Titel	On Lagrange Multiplier Tests in Multidimensional Item Response Theory: Information Matrices and Model Misspecification
Quelle	In: Educational and Psychological Measurement, 78 (2018) 4, S.653-678 (26 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164417714506
Schlagwörter	Item Response Theory; Matrices; Models; Statistical Analysis; Computation; Monte Carlo Methods + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Matrizenrechnung; Analogiemodell; Statistische Analyse; Monte-Carlo-Methode
Abstract	Lagrange multiplier (LM) or score tests have seen renewed interest for the purpose of diagnosing misspecification in item response theory (IRT) models. LM tests can also be used to test whether parameters differ from a fixed value. We argue that the utility of LM tests depends on both the method used to compute the test and the degree of misspecification in the initially fitted model. We demonstrate both of these points in the context of a multidimensional IRT framework. Through an extensive Monte Carlo simulation study, we examine the performance of LM tests under varying degrees of model misspecification, model size, and different information matrix approximations. A generalized LM test designed specifically for use under misspecification, which has apparently not been previously studied in an IRT framework, performed the best in our simulations. Finally, we reemphasize caution in using LM tests for model specification searches. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01